Open Access
Issue
EPJ Web Conf.
Volume 345, 2026
4th International Conference & Exposition on Materials, Manufacturing and Modelling Techniques (ICE3MT2025)
Article Number 01065
Number of page(s) 13
DOI https://doi.org/10.1051/epjconf/202634501065
Published online 07 January 2026
  1. R. Tepfers, Cracking of Concrete Cover along Anchored Deformed Reinforcing Bars, Magazine of Concrete Research, 31(106), 3–12, (1979). https://doi.org/10.1680/macr.1979.31.106.3 [Google Scholar]
  2. M., Mazumder, W., Xu, & R., Al-Mahaidi, Analytical Bond–Slip Model for Deformed Bars in Concrete under Flexure and Axial Loads, Engineering Structures, 180, 655–669, (2019). https://doi.org/10.1016/j.engstruct.2018.11.040 [Google Scholar]
  3. P., Feng, Z., Wang, & Y., Zhang, Experimental and Numerical Study on the Bond–Slip Behavior of High-Strength Steel Bars in Lightweight Ultra-High-Performance Concrete, Construction and Building Materials, 228, 116795, (2019). https://doi.org/10.1016/j.conbuildmat.2019.116795 [Google Scholar]
  4. W., Zheng, L., Li, & Y., Ding, Bond–Slip Behavior of Ribbed Steel Bars in Engineered Cementitious Composites: Experimental Analysis and Constitutive Model, Cement and Concrete Composites, 113, 103727, (2020). https://doi.org/10.1016/j.cemconcomp.2020.103727 [Google Scholar]
  5. S., Xu, L., Wang, & Y., Ma, Bond–Slip Properties of Partially Embedded Steel Tubes in Reactive Powder Concrete, Engineering Structures, 202, 109846, (2019). https://doi.org/10.1016/j.engstruct.2019.109846 [Google Scholar]
  6. Y., Zang, Z., Guo, & Y., Li, Effects of Bar Diameter and Anchorage Length on Bond– Slip Behavior under Freeze–Thaw Cycles, Cold Regions Science and Technology, 176, 103105, (2020). https://doi.org/10.1016/j.coldregions.2020.103105 [Google Scholar]
  7. S., Bhowmik, & B., Bhattacharjee, Electro-Mechanical Impedance-Based Structural Health Monitoring of Concrete Using PZT Sensors: A Review, Sustainable Materials and Technologies, 22, e00108, (2019). https://doi.org/10.1016/j.susmat.2019.e00108 [Google Scholar]
  8. J., Yu, X., Zhang, & Y., Wu, Machine Learning–Enhanced Damage Detection in Concrete Structures Using EMI-Based Features, Sensors, 21(4), 1123, (2021). https://doi.org/10. 3390/s21041123 [Google Scholar]
  9. P.V. Ramana, High-Rise Structural Stalling and Drift Effect Owe to Lateral Loading, Materials Today: Proceedings: 38p5, 2915-2923, (2021). DOI: 10.1016/j.matpr.2021.11.209 [Google Scholar]
  10. M., Patodiya, A., Meena, & P. V., Ramana, Mammoth blast effect on reinforced concrete asymmetrical structure, In AIP Conference Proceedings (Vol. 2943, No. 1). AIP Publishing, (2023). https://doi.org/10.1063/5.0182961 [Google Scholar]
  11. J. S., Chou, & A. D., Pham, Enhanced artificial intelligence for ensemble approach to predicting high performance concrete compressive strength. Construction and Building Materials, 49, 554-563, (2013). DOI: 10.1016/j.conbuildmat.2013.08.078 [Google Scholar]
  12. R., Kazemi, Artificial intelligence techniques in advanced concrete technology: A comprehensive survey on 10 years research trend. Engineering Reports, 5(9), e12676, (2023). https://doi.org/10.1002/eng2.12676 [Google Scholar]
  13. G. U., Alaneme, K. A., Olonade, & E., Esenogho, Critical review on the application of artificial intelligence techniques in the production of geopolymer-concrete. SN Applied Sciences, 5(8), 217, (2023). DOI: 10.1007/s42452-023-05447-z [Google Scholar]
  14. Y., Feng, M., Mohammadi, L., Wang, M., Rashidi, & P., Mehrabi, Application of artificial intelligence to evaluate the fresh properties of self-consolidating concrete. Materials, 14(17), 4885, (2021). DOI: 10.3390/ma14174885 [Google Scholar]
  15. M. N., Amin, W., Ahmad, K., Khan, A., Ahmad, S., Nazar, & A. A., Alabdullah, Use of artificial intelligence for predicting parameters of sustainable concrete and raw ingredient effects and interactions. Materials, 15(15), 5207, (2022). https://www.mdpi.com/1996-1944/15/15/5207# [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.